A process simulation refers to the imitation of a procedure for the purposes of a study, test, or experiment. It often comes in handy in a laboratory when trying to handle the difficulties of a complicated chemical process because a simulation mimics real results.
Generally, it translates a chemical process into a mathematical model, complete with energy and mass balances – taking into account transport, chemical kinetics equations, and phase equilibrium. The aim is to predict behaviors and results when all you have is preliminary data about the process.
Below, we review the basic Chemical process simulation software and types.
Chemical Process Simulation Types
The general types of chemical process simulations you can use are:
- Dynamic State Process Simulation
The dynamic state process simulation is an extension of another simulation – the steady-state simulation. It introduces time dependence into the chemical model through derivative terms, allowing you to make predictions in real-time.
- Steady-State Process Simulation
The steady-state process simulation is independent of time and happens in an equilibrium state. It determines the system’s operating conditions and optimal design parameters to complete an energy and mass balance.
Chemical Process Simulations Applications
Process simulations are very useful in the scientific world and can be applied to the following areas:
· AP Monitor
The AP Monitor simulation applies non-linear predictive control and dynamic simulation in data reconciliation for MATLAB and Python.
· Advanced Simulation Library
The Advanced Simulation Library completed real-time optimization, data reconciliation, and data validation. It also utilizes predictive control and virtual sensing.
The Cycle-Tempo simulation program analyzes and optimizes thermodynamic systems and is used in heat and electricity production and refrigeration.
The BATCHES program simulates multipurpose and multiproduct batch processes and is used in scheduling and chemical design.
Chemical process simulation software and types identify and overcome the challenges of a chemical process by creating imitation models and solutions in real-time. This allows scientists to attempt processes with only preliminary data and make adjustments as necessary.
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